Review of Development and Application of Digital Image Correlation Method for Study of Stress–Strain State of RC Structures

Yaroslav Blikharskyy, Nadiia Kopiika, Roman Khmil, Jacek Selejdak, Zinoviy Blikharskyy
2022 Applied Sciences  
Reliable assessment and prediction of the technical condition of reinforced concrete structures require accurate data of the stress–strain state of the structure at all stages of loading. The most appropriate technique to obtain such information is digital image correlation. Digital image correlation is a class of contactless methods which includes the following stages: obtaining an image from a studied physical object, saving it in digital form, and further analysis in order to obtain the
more » ... sary information about the stress–strain state of the structure. In this research, a detailed analysis of theoretical and experimental findings of digital image correlations was conducted. In the article, the main areas of scientific interest and computational approaches in digital image correlation issues were identified. Moreover, comparative analysis of alternative non-contact techniques, which also could be used for diagnostics of RC structures' stress–strain state was conducted. The novelty of the study consists of a thorough comparative analysis with the indication of specific features of digital image correlation, which determine its wide application among the other similar methods. On the basis of the conducted literature review, it can be seen that the digital image correlation technique has gone through multi-stage evolution and transformation. Among the most widely studied issues are: image recognition and matching procedures, calibration methods and development of analytical concepts. The digital image correlation technique enables us to study cracking and fracture processes in structural elements, obtaining the full field of deformations and stresses. Further development of image processing methods would provide more precise measuring of stress–strain parameters and reliable assessment of structural behavior.
doi:10.3390/app121910157 fatcat:cnr5or2zwbbu5dnns3uqu3zixq